Abstract
In the social sciences, it is often useful to introduce latent variables and use structural equation modeling to quantify relations among observable and latent variables. This paper presents a manual, describing how to estimate structural equation models in a Bayesian approach with R. Parameter estimation follows a Gibbs sampling procedure, generating draws from the full conditionals of the unknown parameters. The manual is divided into two main parts. The first part presents an introduction to the estimation of structural equation models with R. The second part describes a method for simulating data of a structural equation model and the appendix contains the derivation of the full conditional distributions.
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